The platform is powered by EOS Engine and is based on a multi-level deep learning architecture that targets land cover and classifies crop types from multi-source satellite imagery. The key element of the architecture is an unsupervised neural network that is used for optical imagery segmentation and missing data restoration.

It supports many types of earth observation data sets and capable of on-the-fly analytics processing. The platform can automatically remove cloud cover and shadows as well as extract valuable information on a different scales with the processing of large-area data. Additionally, the tool includes both historical and current observations. This allows for quick identification of a field’s performance throughout the growing season as well as high-risk areas affected by droughts, floods, hail, etc.

Interestingly the app can be licensed as a White-Label, providing EOS partners with cloud-based services for their own users to increase interactions across the whole farming value chain. The platfrom can be customized as well as integrated with 3rd party systems through EOS API.

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I'm a professional always thinking outside the box and a self-confessed gadget addict. As a son of a professor of cartography I was surrounded by maps all my life and as a result spatial way of thinking and seeing reality is naturally embedded in who I am.